Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control
Paper recorded by Signals 4 on 2026-09-28 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-28 on arXiv · recorded by Signals 4 on 2026-09-29
Category: cs.LG · 机器学习 · first seen 2026-09-29
Abstract
We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances. The framework connects classical disturbance-accommodating control (DAC) to recent last-layer adaptive disturbance-rejection methods. Specifically, we introduce a statistically principled hard expectation-maximization (hard-EM) procedure, with a Kalman smoother in the hard
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Cite this page: Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control: the #3 most recent of 322 cs.LG papers we have recorded (as of 2026-09-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/statistical-learning-of-contractive-dynamical-representations-for-composite-adap.html
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